Computational neural network methodology

Duprat, A. F., Huynh, T. Dreyfus, G. (1998). Toward a principled methodology for neural network design and performance evaluation in QSAR. Application to the prediction of logP. J. Chem. Inf. Comput Sci. 38,586-94. 

A different way of encoding the structure consists of using chemical graphs as input for a recursive neural network (RNN). The RNN automatically encodes the structural information depending on the computational problem at hand. [36] Again, the influence of the anion was overlooked, for this methodology was applied to a set of ILs based on pyridinium bromide. 

This work combines the design of experiment (DOE) methodology and neural network to develop a computational-intelligence-based injection molding quality predictor. The DOE obtains the optimal process windows... 

Biological methodology in our everyday IT promises a kind of uniformity and interoperability that will encompass both medical and nonmedical computing, and mediation with implanted chips. This biology in IT is a methodology apart from neural nets, which are smart learning networks based on brain principles, represented in software. The changes of interest here are at the hardware level. It is probable that all traditional computer system architecture, medical and otherwise, will soon make the first steps to a transition to a deeper... 

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